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this is an error occured to me while running this command:npm install -g edge-impulse-cli --force

TinyML

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Meehad last edited by
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salmanfaris @Meehad last edited by

@Meehad Could you please share the OS version and node JS , npm version you have?
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Raja1234 @salmanfaris last edited by

@salmanfaris Hello sir. I am facing the same problem.

OS: Windows 10 Home
NodeJS: v20.9.0
npm: 10.2.4
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Hi @sanal143, Welcome to the MakerGram community .

Does your training data contain noise data similar to the data you are inferencing? and May I know, what kind of hardware you are using to run the model. Thanks

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I'm developing an audio classification project with four classes using an RNN with LSTM. While the model performs well in classifying audio in silent environments, it struggles with noisy situations like crowds or disturbances. How can I train the model more robustly to accurately predict classifications in such challenging environments?

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A

@salmanfaris No, I haven't made any progess on the matter

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Hi @amalkrishnam3, Were you able to make any progress?

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I have been working on a project . In which I want to capture data using the PDM mic and trasmit it through the BLE available . I am new to hardware and these sensors so I am unable to make sense of the data I am reciving on the other side(central) that is my mobile device(iphone X) with BlueLight application. I am able to find a service and I am reciving some form of hex code,but I don't know how to convert it to wave files or don't know whether it's possible or not .

If you guys have any idea or any resources that could help please do share.

I am attaching my code below :
#include <ArduinoBLE.h> #include <mic.h> // microphone library // Microphone Settings #define DEBUG 1 #define SAMPLES 800 mic_config_t mic_config = { .channel_cnt = 1, .sampling_rate = 16000, .buf_size = 1600, .debug_pin = LED_BUILTIN }; NRF52840_ADC_Class Mic(&mic_config); int16_t recording_buf[SAMPLES]; volatile static bool record_ready = false; // Updated UUIDs #define SERVICE_UUID "19B10000-E8F2-537E-4F6C-D104768A1214" #define CHARACTERISTIC_UUID_AUDIO "19B10001-E8F2-537E-4F6C-D104768A1214" // BLE Service and Characteristic BLEService audioService(SERVICE_UUID); // Corrected initialization with explicit value size and fixed length flag BLECharacteristic audioDataCharacteristic(CHARACTERISTIC_UUID_AUDIO, BLERead | BLENotify | BLEWrite, sizeof(recording_buf), true); void setup() { Serial.begin(115200); while (!Serial) delay(10); Serial.println("Initializing microphone..."); Mic.set_callback(audio_rec_callback); if (!Mic.begin()) { Serial.println("Mic initialization failed"); while (1); } Serial.println("Mic initialized."); Serial.println("Initializing BLE..."); if (!BLE.begin()) { Serial.println("Failed to start BLE!"); while (1); } BLE.setLocalName("SCT Audio"); BLE.setAdvertisedService(audioService); audioService.addCharacteristic(audioDataCharacteristic); BLE.addService(audioService); // Corrected writeValue call with explicit casting audioDataCharacteristic.writeValue((uint8_t)0); BLE.advertise(); Serial.println("BLE Peripheral is now advertising"); } void loop() { BLEDevice central = BLE.central(); if (central) { Serial.println("Connected to central device"); while (central.connected()) { if (record_ready) { // Plot the audio data in the Serial Plotter for (int i = 0; i < SAMPLES; i++) { Serial.println(recording_buf[i]); } // Transmit the audio data audioDataCharacteristic.writeValue((uint8_t*)recording_buf, 2 * SAMPLES); Serial.println("Audio data transmitted over BLE"); record_ready = false; } } Serial.println("Disconnected from central device"); } } static void audio_rec_callback(uint16_t *buf, uint32_t buf_len) { static uint32_t idx = 0; for (uint32_t i = 0; i < buf_len; i++) { recording_buf[idx++] = buf[i]; if (idx >= SAMPLES){ idx = 0; record_ready = true; break; } } }

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